Control of the multimillennial wild
fire size in boreal
North America by spring climatic conditions
Adam A. Alia,b,1,2, Olivier Blarquezb,c,1, Martin P. Girardind, Christelle Hélya,e, Fabien Tinquautf, Ahmed El Guellabb,c, Verushka Valsecchia,e, Aurélie Terrierc, Laurent Bremonda,e, Aurélie Genriesb,c, Sylvie Gauthierd, and Yves Bergeronb,c aCentre de Bio-Archéologie et d’Ecologie, Unité Mixte de Recherche (UMR) 5059 Centre National de la Recherche Scientifique (CNRS), Université Montpellier 2, Institut de Botanique, F-34090 Montpellier, France;bNatural Sciences and Engineering Research Council of Canada Industrial Chair in Sustainable Forest Management, Forest Research Institute, Université du Québec en Abitibi-Témiscamingue, Rouyn-Noranda, QC, J9X 5E4 Canada;cCentre d’Etude de la Forêt, Université du Québec à Montréal, Montreal, QC, H3C 3P8 Canada;dRessources Naturelles Canada, Service Canadien des Forêts, Centre de Foresterie des Laurentides, Québec, QC, G1V 4C7 Canada;ePaléoenvironnements et Chronoécologie (PALECO), École Pratique des Hautes Études (EPHE), Institut de Botanique, F-34090 Montpellier, France; andfCentre Européen de Recherche et d’Enseignement des Géosciences de l’Environnement, UMR 7330 CNRS, Université Aix-Marseille, F-13545 Aix en Provence Cedex 4, France
Edited by Robert E. Dickinson, University of Texas at Austin, Austin, TX, and approved October 24, 2012 (received for review March 1, 2012)
Wildfire activity in North American boreal forests increased during
the last decades of the 20th century, partly owing to ongoing human-caused climatic changes. How these changes affect
re-gionalfire regimes (annual area burned, seasonality, and number,
size, and severity offires) remains uncertain as data available to
explorefire–climate–vegetation interactions have limited
tempo-ral depth. Here we present a Holocene reconstruction offire
re-gime, combining lacustrine charcoal analyses with past drought
andfire-season length simulations to elucidate the mechanisms
link-ing long-termfire regime and climatic changes. We decomposed fire
regime into fire frequency (FF) and biomass burned (BB) and
recombined these into a new index to assessfire size (FS)
fluctua-tions. Results indicated that an earlier termination of thefire
sea-son, due to decreasing summer radiative insolation and increasing
precipitation over the last 7.0 ky, induced a sharp decrease inFF
andBB ca. 3.0 kyBP toward the present. In contrast, a progressive
increase ofFS was recorded, which is most likely related to a
grad-ual increase in temperatures during the springfire season.
Con-tinuing climatic warming could lead to a change in thefire regime
toward larger spring wildfires in eastern boreal North America.
Canada
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drought code|
global circulation model|
paleoclimateR
ecent increases in wildfire frequency and biomass burning in boreal regions in response to ongoing climate warming threaten the carbon sink strength of native ecosystems and, by extension, further contribute to global warming (1). Up-to-date model-basedfire predictions indicate that these trends will per-sist in the coming decades as atmospheric greenhouse gas con-centrations will attain unprecedented levels by the end of this century (2, 3). However, model-basedfire predictions depend on data collected over short periods—usually less than 100 y—that do not cover a wide range offire–climate interactions and feedback processes arising from changes in vegetation features. This reduces the robustness offire predictions, which must therefore be supple-mented by paleoecological investigations (4). These investigations often integrate several scientific disciplines, datasets, approaches, and methodologies, thereby providing a robust assessment of how recent trends infire activity fit into the long-term perspective.Until now, paleofire reconstructions based on charcoal lacus-trine deposits have mostly focused on describing pastfire activity in terms of frequency and biomass burning (5). Here we address an additional aspect offire history and fire–climate relationships, namely, the change infire size over periods of substantial climate change. To do this, we use sedimentary charcoal records extracted from nine kettle lakes located in the eastern North American boreal forest and model simulations of past climate. We in-troduce a new metric, developed from the combination of the fire frequency and biomass burning components, which allows us to assess the mean biomass burned perfire. We report on the relationship between components of this index with respect to
fire characteristics such as size, and we explore its relationship to long-term regional drought conditions andfire-season length. Sediment Core Locations
The nine lakes are located along a 350-km east–west transect southeast of the James Bay area (50°N, 80°W;Fig. S1). The lakes were chosen because of their similar size, maximum depth, and shape (Table S1). These physical similarities and the spatial prox-imity of sites within a unique ecozone (dense coniferous boreal forest) made it possible to construct regional composite records offire regime variability over the last 7,000 y (hereafter 7 ky;Fig. S2). After the deglaciation∼8 ky ago (kya) depending on areas, trees and woodlands began to rapidly colonize the area without going through an initial tundra phase (6). Picea mariana (Mill.) B.S.P. has been the main conifer species dominating the regional vegetation (P. mariana–feathermoss bioclimatic zone) since at least 7.5 kya (7, 8). Recent paleofire reconstructions in the western part of the study zone have identified a gradual reduction in fire frequency over the last 3.0 ky (9) in response to a reduction in the length of the fire season (10). Dendrochronological inves-tigations corroborate thisfinding, highlighting an increase in the fire cycle since the end of the Little Ice Age (11).
Results and Discussion
Paleofire Regime.Variations in charcoal accumulation rate (CHAR,
charcoal load per time unit, e.g., mm−2·cm−2·y−1) provide a continuous record of past localfire activity within the sampling resolution of the sediment record. For this study, we used the pooled CHAR data from the nine kettle lakes to infer past regional biomass burning (RegBB; Materials and Methods). A comparison of RegBB with a published stand-replacingfire history (11), in an area encompassing 15,000 km2, indicated that RegBB tracked well mid- to long-term changes in the annual proportion of area burned in the study zone (Fig. S3). The RegBB recon-struction thus appears to be an adequate proxy for inferring past regional losses of forest cover. RegBB values showed that there was a significant increase in biomass burning between 6.0 and 4.0 kyBP, followed by relative stability from 4.0 to 2.0 kyBP and a reduction during the last 1.5 ky (Fig. 1A).
Author contributions: A.A.A., S.G., and Y.B. designed research; A.A.A., O.B., M.P.G., and C.H. performed research; A.A.A., O.B., M.P.G., C.H., F.T., A.E.G., V.V., A.T., L.B., and A.G. analyzed data; and A.A.A., O.B., M.P.G., and C.H. wrote the paper.
The authors declare no conflict of interest. This article is a PNAS Direct Submission.
Freely available online through the PNAS open access option.
1A.A.A. and O.B. contributed equally to this work.
2To whom correspondence should be addressed. E-mail: ali@univ-montp2.fr.
This article contains supporting information online atwww.pnas.org/lookup/suppl/doi:10. 1073/pnas.1203467109/-/DCSupplemental.
From lacustrine charcoal data it is also possible to deduce the regional fire frequency (RegFF) by analyzing peak components of the total CHAR (i.e., significant peak above the background; Materials and Methods). As illustrated in Fig. 1B, mean RegFF underwent a gradual increase between 6.0 and 5.0 kyBP, fol-lowed by 3.0 ky of relative stability, with a mean of 0.0097fire·y−1 (90% confidence interval (CI): [0.0080, 0.0120]). This value of RegFF corresponds to a meanfire-free interval (MFI) of 103 y [83, 125]. A decrease in RegFF occurred between 3.0 and 0 kyBP (Fig. 1B). The present-day RegFF (0 ky, computed over the last 100 y) is estimated to be 0.0058fire·y−1[0.0046, 0.0072], i.e., a MFI of 180 y [139, 217]. This MFI is close to thefire cycle es-timate derived from the stand-replacingfire history of the study zone (i.e., 171 y with 95% CI [152, 194]) (11).
Usually, fire size and severity (i.e., the loss of tree crown canopy and surface and belowground organic matter during a fire) correspond to metrics related to a given fire event and they may be defined in different ways (12). We consider that fire size and severity are related to the temporal trajectory of mean bio-mass burned perfire, reflecting part of the loss of organic matter (RegBB), modulated by the number offires through time (RegFF). Both severity and size of fires are correlated in eastern boreal North America: Large stand-replacing wildfires (>200 ha) are often severe, with high tree mortality (11, 13). However, below we limit our discussion tofire size on the basis of the observed correlation between RegBB and long-term changes in the area burned inferred fromfire history studies (14) (SI Text). We used the ratio between RegBB and RegFF to characterize the temporal changes in fire size (Fig. 1C; hereafter FS index; Materials and Methods) at a regional scale:
FS¼ RegBBRegFF: [1]
Herein, FS index values<1 are indicative of a lower mean bio-mass burned perfire owing to smaller fire sizes, and vice versa. The use of the FS index as a proxy for meanfire size is supported by its significant correlation to the changes in the median of the magnitude of CHAR peaks (PEAKMED, Fig. 1D) from 7.5 ky to present (r= 0.42, 95% bootstrap confidence interval with cor-rection for autocorrelation in data= [0.28, 0.54]). High ampli-tude of CHAR peak should represent largefire events within the
−1 0 1 0.004 0.006 0.008 0.010 0.012 0.014 0.6 0.8 1 1.2 1.4 10−2 10−1 e ab bc d bc abc d Biomass burning
RegBB (no unit)
c c b a a a b Fire frequency RegFF (Fire.yr -1 ) b d −0.5 0 0.5 −10 0 10 20 30 0 1 2 3 4 5 6 7 -1 0 1
Age (cal. k-yrs BP)
P Annual P Spring P Summer T Annual T Spring T Summer 0 10 20 30 Spring Summer 120 140 160 180 Fire season length
(no. days)
MarchApril MayJune
JulyAugust September
Fire season length
Precipitation
Insolation
Temperatures Fire season length (no. days anomalies)
Precipitation anomalies (mm.day -1) 45°N Insolation anomalies from 1950 AD (W.m -2 ) Temperature anomalies (°C) 0 1 2 3 4 5 6
7 Age (cal. k-yrs BP)
Fire size
FS index (no unit) 1000 yrs500 yrs
200 yrs b d a bc c b cd d
log(median CHAR peak)
Median CHAR peaks
A
B
C
D
E
F
G
H
Fig. 1. Reconstructedfire regime history based on the analysis of lacustrine charcoal deposits. (A) Biomass burning (RegBB) using total charcoal influx. Black line corresponds to the smoothing values using a LOWESS function (500-y time window). The yellow area corresponds to the 90% bootstrap confidence intervals (BCI). The median value for the sequence is represented by the red dashed line. Detected trends were confirmed by box-plot analysis carried out for each 1,000-y period; significance between millennia was assessed using the Wilcoxon rank sum test. A stable amount of biomass that
burned from 5.5 to 1.5 kya and a decrease thereafter are recorded. (B) Fire frequency (RegFF) using the peak components of total charcoal influx, dis-playing a significant decrease in fire frequency after 3.0 kya. A Gaussian kernel smoothing with a bandwidth of 500 y was used to illustrate the RegFF trend. (C) Fire size (FS index) computed from the ratio RegBB/RegFF and indicating a significant shift from frequent but small wildfires to infrequent but larger events. The black line represents the median of simulated FS index for the 500-y bandwidth; the 200- and 1,000-y bandwidths are represented by the dashed red and purple lines, respectively (Materials and Methods). (D) Median CHAR peak values (PEAKMED) computed across a moving window of 23fire events (∼500-y window; Materials and Methods). PEAKMEDis herein used as a proxy forfire size. The median value for the sequence is repre-sented by the red dashed line. A gradual increase in PEAKMEDwas recorded up to 1.5 kya. (E) Fire season length assessed on the basis of the number of days with simulated monthly means of daily drought code (DC) values higher than 80 units, showing a decrease infire-season length over the last 7000 y (spring and summer DCs are indicated by dotted and dashed lines, re-spectively). Error bars denote the SDs. (F) Simulated annual and seasonal precipitation by the UGAMP model (anomalies relative to preindustrial control period (0 kyBP) assumed to be representative of the present-day conditions). (G) Monthly radiative insolation at 45°N (35) showing a decrease during the summer months (July to September) and an increase during the spring months (April to June). (H) Simulated annual and seasonal air tem-peratures by the UGAMP model (the same preindustrial period for the present-day reference and anomaly calculation), showing a significant in-crease in spring temperatures during the last 3.0 ky.
ENVIRONM
ENTAL
potential charcoal source area (15). Our interpretation offire size fluctuations is based on both FS index and PEAKMEDtrends.
Before 4.5 kyBP, FS index values were mostly<1 (Fig. 1C). The total biomass burned likely resulted mostly from numerous smallfires (low PEAKMED; Fig. 1D). During the period extending between 4.5 kyBP and 2.5 kyBP, FS index values were close to 1 and RegBB varied in the same range as RegFF. The period was likely to be one in which an intermediate fire regime was estab-lished, where RegBB resulted from small to largefires (PEAKMED mostly varied around the long-term median). This was followed by a gradual increase in the FS index until ca. 1.5 kyBP. The total biomass burned likely resulted mostly from large fires (high PEAKMED; Fig. 1D). The last 1.5-ky period was characterized by a decrease in both RegFF and RegBB: The FS index decreased, reaching values close to 1 (PEAKMED was also below the long-term median). Below we provide some potential explanations for the trajectory recorded infire size, with the climatic hypothesis as the most plausible one.
Climatic Hypothesis.In boreal forests, large-fire years occur as a
result of increased late-season burning associated with warm springs followed by dry summers (1, 16). Unsynchronized changes between spring and summer conditions may hence bring unexpected changes in fire metrics like total biomass burned, number offires, and mean fire size. Such complex effects were tested by analyzing data extracted from the UK Universities Global Atmospheric Modeling Program (UGAMP) (17) general circulation model (GCM) and comparing the modeled regional drought conditions and fire-season length (computed for each 1.0-ky period) with RegBB, RegFF, and the FS index. The fire-season length (Fig. 1E) was assessed from the cumulative num-ber of dry days having simulated drought code (DC) (Materials and Methods) values above the threshold of 80 units (10). Al-though a slight increase in simulatedfire-season length occurred during the period between 4.0 and 2.0 kyBP, the data confirmed the general multimillennial decreasing trend over the past 7 ky reported by previous studies (10). This long-term modification in simulatedfire-season length appears to result from an increase in annual precipitation (Fig. 1F and Table 1) along with a decrease in summer radiative insolation (Fig. 1G and Table 1).
On the basis of exploratory expressions of the long-term cor-relations linking fire regime components to climatic variability and orbital forcing (Table 1 andTable S2andS3), a conceptual scheme can be suggested (Fig. 2). In eastern North American boreal forests, changes in Holocenefire regime were driven ul-timately by orbital forcing through spring (April to June) and summer (July to September) radiative insolation. The gradual increase in precipitation, coupled with a decrease in summer insolation, had a negative impact on RegFF and RegBB, likely
from less-efficient ignition. The FS index was positively driven by spring climatic conditions, notably through insolation-driven increases in temperature early in thefire season (Table 1). Such evidence for a temperature influence on the size of early-season fires is to our knowledge lacking. To examine whether this effect was plausible, we collected data on sizes of lightning-causedfires in P. mariana–feathermoss forests recorded from 1973 to 2009 and analyzed their correlation to monthly mean land temper-atures (SI Text). Results from this analysis show that the mean fire size in the early-fire season is indeed highly correlated to June temperature: A tripling of the meanfire size occurs with each 1 °C increment (Fig. 3). This result is consistent with data from western United States forests and P. mariana forests in Alaska, where it is reported that large (or severe)fire years occur as a result of dry fuel conditions and greater fuel availability occurring with earlier seasonal ice thaw (1, 18). Thus, insolation-driven increases in temperature early in the fire season could have contributed to increasing meanfire size over the past 7 ky in our study zone. The shift in FS index has occurred despite the increase in spring and annual precipitation during the Late Holocene, which would have been insufficient to compensate for the effect of spring warming. Intraseasonal variations in rain events distribution may also explain the low impact of pre-cipitation during the springfire season.
Vegetation Pattern Hypothesis.Ecological processes may be held
responsible for the changes observed in the FS index. A decrease in fire frequency during the Late Holocene (after 4.0-ky BP) could have favored fuel-load continuity and accumulation (19– 21), enhancing the occurrence of large stand-replacing wildfires (22). However, the realism of this vegetation feedback on fire size is questionable when confronted with the existing literature on the subject. Indeed, it is generally accepted in the boreal coniferous forest that the probability of burning is independent of stand age and fuel load after canopy closure at 15 or 20 y (23). Alternatively, changes in vegetation composition toward more fire-prone fuel types could have contributed to the increase in fire size during the Late Holocene (24). Still, pollen records from the study zone suggest that forest composition has remained in a stable state, with woodlands dominated by P. mariana since at least 7.5 kyBP (e.g., ref. 8). Nevertheless, slight changes in spe-cies abundance, including that offire-prone species P. mariana and Pinus banksiana Lamb. (25), could have played a role in the fire size fluctuations recorded by the FS index. This long-term feedback of landscape vegetation on wildfire size dynamics must be formally tested by further paleovegetation reconstructions that could infer and quantify past vegetation structuring.
Table 1. Pearson’s correlation coefficients between reconstructed fire regime history and main climatic variables
Variables Fire season length Spring temperatures Spring precipitation Annual precipitation March insolation Summer insolation
(July, August, September) RegBB RegFF FS index
Fire season length 1
Spring temperatures −0.576 1 Spring precipitation −0.832** 0.670** 1 Annual precipitation −0.913*** 0.827** 0.865*** 1 March insolation −0.794** 0.781** 0.740** 0.836*** 1 Summer insolation 0.823** −0.792** −0.816** −0.865*** −0.976**** 1 RegBB 0.104 −0.237 0.167 −0.096 −0.472 0.316 1 RegFF 0.432 −0.576 −0.267 −0.475 −0.827** 0.723* 0.857** 1 FS index −0.809** 0.753** 0.895*** 0.856*** 0.860**** −0.927**** 0.021 −0.475 1
April to June for spring and July to September for summer. Significant correlation coefficients are in boldface type with P values reported as follows: *P < 0.1; **P< 0.05; ***P < 0.01; ****P < 0.001. Significance was determined using permutation tests with correction for multiple comparisons (SI Text). Sample size is n= 8 millennia.
Conclusion
Our work suggests that the wet climate that characterized the northeastern American boreal forest during the late Holocene (after 3.0 kyBP) was associated with infrequent wildfires, but these were large in extent. The drier climate that characterized the mid-Holocene (before 3.0 kyBP) was associated with a high fire frequency, but fires were smaller than during the Late Ho-locene. Fire frequency and total biomass burning were controlled by summer radiative insolation and annual precipitation, whereas fire size was dependent upon spring temperatures and perhaps also abundance offire-prone species (P. mariana and P. banksiana) at the landscape level. Climatic conditions during the springfire season and the precipitation regime will play a key role in future fire risk. Human-caused global warming will probably lead, as summer insolation did in the past, to drier conditions coupled with an increase in the length of thefire season (26). This may increase fire frequency and area burned. However, our results suggest that larger spring wildfires may also be foreseen with climatic warming. An important question is whether signs of such a change infire regime are currently observable in North America, given the pronounced upward trend in area burned by wildfires observed during the 20th century.
Materials and Methods
RegBB. Total lacustrine charcoal influxes (CHAR, mm2·cm−2·y−1) are commonly used to decipher past biomass combustion at the regional to continental scale (e.g., refs. 27, 28). Here, the composite record of regional biomass burning was constructed by pooling Z-score–transformed individual CHAR series (27) (SI Text). This method allowed us to minimize the bias related to taphonomic processes and the changes in sedimentation rates (SI Text). RegFF. The CHAR peak component of the total charcoal influx, corresponding to the high-amplitude signals of the charcoal series, was used to reconstruct localfire events (SI Text). The CHAR peak component of the total CHAR series is commonly used to infer localfire frequency, i.e., less than 1.3–3.0 km from the lakeshore (29). Each CHAR peak exceeding the threshold is hereafter assumed to be afire episode, which represents one or more fires occurring within the charcoal source area and within the median sampling resolution of each sequence. A kernel density smoothing function was used to de-termine a temporally smoothedfire frequency (FF) for each core, on the basis of individual reconstructedfire events (30), and the mean RegFF was determined on the basis of pooled FF for all lakes (Fig. S4andSI Text). Fire Size Assessment (FS Index). We reconstructed the FS index through time, using the formulation bellow:
FS= X 1;000 i=1 RegBBi+ β RegFFi+ β , N :
RegBBirepresents 1,000 RegBB reconstructions obtained by random resampling of the individual CHAR series, RegFFirepresents 1,000 RegFF reconstructions obtained by random resampling of the local FF series, N is the number of resamplings (n= 1,000), and β is a constant equal to 1. In order to illustrate high to low frequency trends in the FS index, this procedure was reiterated three times using bandwidths equal to 200, 500, and 1,000 y. The 90% confidence intervals are calculated from the true distribution of the 1,000 resampled FS index series and are presented for the 500-y bandwidth only. The FS index must be considered in evaluating the long-term (centennial to millennial timescale) trajectory of mean size offire events at the regional scale and not in charac-terizing the size of individualfires. Also, one should be cautious about the interpretation of potential correlation between FS index and RegFF, as these are linked by definition and therefore a negative correlation can be expected. Magnitude of CHAR Peaks. The magnitude of CHAR peaks can be used as a proxy forfire size and severity (15, 31). Hence, we computed the median of the magnitude of detected CHAR peaks, using a running window of 23 CHAR peak samples from 7.5 kya to the present. The use of 23 CHAR peak samples is equal to a window width of∼500 y. For each window, the median was computed 1,000 times, using a bootstrapping method, and a 90% confidence interval was constructed.
Fire Season Length. We used paleoclimatic simulations provided by the UGAMP (17) to develop a mechanistic understanding of the climatic variations associated
RegFF
Reg BB Fire size
FS index 1 <1 >1 Annual precipitation Spring conditions (T¡, P¡, insolation) Fire-season length (DC) Legend: Positive Negative
Fig. 2. Conceptual scheme of the balance (ratio) between biomass burned (RegBB) andfire frequency (RegFF), defining fire size and their relationships to climate conditions and orbital forcing. We deliberately oriented relations of cause and effect, using arrows from the relationships established using the correlation coefficients presented in Table 1. Signs (colors) refer to sig-nificant positive or negative correlations, respectively. During the Holocene, the FS index has moved along the scale from values<1 to values >1 (Fig. 1C) and it stopped twice around a value of 1, owing to different conditions.
Fig. 3. The effect of mean temperature on mean fire size during early-season burning in P. mariana–feathermoss forests of eastern boreal North America. Fire data were those of the Ministère des Ressources Naturelles et de la Faune du Québec. The period of analysis is from 1973 to 2009. Mean fire size was computed for 18 early seasons (April to June), using a minimum threshold of n= 10 fires y−1; those seasons in which the number offires was below this threshold were excluded from analysis. Ignition of 95% of the sampledfires took place after May 27th (n = 740 fires in total; Lower, sample distributions; correlation between n and meanfire size is Spearman’s r = 0.232, P = 0.347). Error bars represent 90% confidence intervals for the means obtained by bootstrap resampling of thefire samples. The dashed line rep-resents the exponential regression of meanfire size on mean temperature. Temperature data (land only) were those of Climate Research Unit TS 3.1 (32), averaged over the domain encompassing 79.5°W–70.0°W and 48.5°N–52.5°N.
ENVIRONM
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with the reconstructed paleofire regime (SI Text). A downscaling method was conducted by applying the UGAMP anomalies of temperature and pre-cipitation to the Climate Research Unit climatology dataset Times Series (TS) 2.1 (32). Richardson’s (33) weather generator was applied to the simulated time series of monthly temperature and precipitation to derive daily values necessary to compute the DC index of the Canadian Forest Fire Weather Index System (34). A DC value of zero is indicative of saturation and values higher than 400 are indicative of potential deep burning of subsurface heavy fuels.
ACKNOWLEDGMENTS. Financial support was provided by the programs Paléo-environnements, Paléoclimats [Institut Ecologie et Environnement Centre National de la Recherche Scientifique, France] (A.A.A.), the Natural Sciences and Engineering Research Council of Canada (Y.B. and A.A.A.), the Fonds de Recherche Nature et Technologie du Québec (Y.B. and S.G.), the Forest Complexity Modelling program (Natural Sciences and Engineering Research Council, Canada) (O.B.), and the Canadian Forest Service. The re-search was carried out within the framework of the International Associated Laboratory (France–Canada).
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